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A Review on: Spread Spectrum Watermarking Techniques

In the name of GOD. A Review on: Spread Spectrum Watermarking Techniques . Table of contents. Introduction Spread Spectrum communication Cox method Adaptive watermarking Comparison Conclusion. Spread Spectrum Method. Introduction.

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A Review on: Spread Spectrum Watermarking Techniques

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  1. In the name of GOD A Review on:Spread Spectrum Watermarking Techniques

  2. Table of contents • Introduction • Spread Spectrum communication • Cox method • Adaptive watermarking • Comparison • Conclusion

  3. Spread Spectrum Method

  4. Introduction • The first papers on data hiding appeared in the early 1990s. • (LSB) embedding techniques • elementary and non-robust against noise. • The period 1996–1998: • The development of Spread Spectrum method codes • image watermarking (Cox et al. 1997) • Video watermarking (Hartung and Girod 1998 ) • more robust and have been used in several commercial products.

  5. Spread Spectrum Modulation (SSM) • The watermarking problem is analogous to a communication problem with a jammer. • motivated many researchers to apply techniques from SSM (successful against jammers.) • SSM good for military communication systems (secrecy and robustness due to unauthorized person) • The jamming problem: • Standard radio or TV communication system: • TX sends a signal in a relatively narrow frequency band. • Inappropriate in a communication problem with a jammer. • The jammer would allocate all his power to that particular band of frequencies.

  6. Spread Spectrum Modulation (Cont’d) the message is spread over a wide frequency BW. The SNR in every frequency band is small (difficult to detect) • SSM system: • Allocates secret sequences (with a broad frequency spectrum) to the TX, which sends data by modulating these sequences. • RX demodulates the data using a filter matched to the secret sequences. (The codes used for spreading have low cross correlation values and are unique to every user) • Attacker must spread jamming power over all D dimensions. • Owner knows which N dimensions are important.

  7. Advantages of Spread Spectrum Communication • Resist intentional and unintentional interference. • Can share the same frequency band with other users • Protect the privacy, due to the pseudo random code sequence.

  8. Spread Spectrum technique for watermarking • Adopt ideas from spread spectrum communication • The WM message is spread over a wide frequency bandwidth (spectrum of the host image) • Hide a D-dim. signal (information to embed) in an N-dim. space (part of original document), N >> D • The SNR in every frequency band is small (difficult to detect) • RX knows the place of WM concentrate weak signals to high SNR output. • Generate noise like carrier or hopping sequence with cryptographically secure methods (Security ) • if parts of the message are removed from several bands, enough information is present in other bands to recover the message • it is difficult to remove the message completely without entirely destroying the cover (robustness)

  9. Embedding a Direct-Sequence Spread-Spectrum Watermark

  10. Recovering a Direct-Sequence Spread Spectrum Watermark

  11. Secure Spread Spectrum Watermarks for Multimedia • The first spread spectrum watermarking method based on DCT • Proposed by Cox. • Cox et al.asserted that in order for a watermark to be robust, it need to be placed in the most significant part of the image. • the watermark will be composed of random numbers drawn from a Gaussian N(0,1) distribution

  12. Insertion of the watermark • Insert X (WM) into V (DCT coeffs.) results in V’ • 3 natural formula for computing V’: • The general form: • Do not provide a solution for how to compute in order to maximize the robustness of the watermark. • (set =0.1) • How choose N?

  13. Informed Watermarking Method of Cox et al.

  14. Secure Spread Spectrum Watermarks for Multimedia • Evaluating the similarity of the watermark • The extracted watermark might differ from the original watermark. • one should decide on a threshold T, and compare • Set T to minimize the false positives and false negatives.

  15. Threshold Comparison • Reducing False Positive (FP) error • Selecting the appropriate threshold  Select Threshold =6

  16. Experiments Watermarked image

  17. Compression and cropping attacks

  18. Uniqueness of the Watermark

  19. Disadvantages • The need to have the original image to be able to detect the watermark. • Since the DCT transform is based on the whole image , the transform does not allow for any local spatial control of the watermark. • Does not provide a maximum use of the human visual system

  20. Image Adaptive Watermarking • The image adaptive DCT • based on 8x8 DCT framework (Wolfgang et al.) • Wavelet (Podilchuk and Zheng) • Use Just Noticeable Difference (JND) Matrix. • The JND is derived from image independent frequency sensitivity and image dependent luminance sensitivity and contrast masking. • This assists in determining the maximum amount of watermark signal that can be tolerated. • the goal is to place the maximum strength watermark sequence (Why?).

  21. Adaptive Image Watermarking • HVS models as image Adaptive weights of watermarks: 2) HVS models as filters of Perceptually important image components: 3) A combination of Previous two methods.

  22. Podilchuk-Zeng (P&Z) Method Watermark Embedding: : threshold calculated for each level & frequency orientation by Watson for 9.7 Daubechies Filters.

  23. Watermark Detection • Watermark detection: • Again use similarity and appropriate threshold which is designed to balance false positives and false negatives.

  24. Experiment 1 (uniform image)

  25. Experiment 2 (non-uniform image)

  26. Podilchuk method (Attacks)

  27. SSIS Method

  28. Results watermarked Original

  29. JPEG Attack

  30. Noise Attack

  31. Conclusion • Spread spectrum communication • watermarking problem is analogous to a communication problem with a jammer. • the WM message is spread over a wide frequency bandwidth (spectrum of the host image) • Cox method. • Adaptive watermarking

  32. References [1] I. J. Cox, J. Kilian, T. Leighton, T. Shamoon, “Secure spread spectrum watermarking”, in IEEE Transaction on Image Processing, vol. 6. 1997. [2] C. I. Podilchuk and W. Zeng, “Image adaptive watermarking using visual models”, IEEE journal on selected areas in communication, vol. 16, No. 4, pp. 525-538, May 1998. [3] L. M. Marvel, C. G. Boncelet, C. T. Retter, “Spread Spectrum Image Steganography,” IEEE Trans, on Image process., vol 8, no. 8, Aug. 1999. [4] W. Lu, H. T. Lu, F. Chang, “Chaos-Based Spread Spectrum Robust Watermarking in DWT Domain,” in Proc. Int. Conf. on Machine Learning and Cybernetics, Guangzhou, Aug, 2005.

  33. Any Question?

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